Leveraging intelligence from network CDR data for interference aware energy consumption minimization

Cell densification is being perceived as the panacea for the imminent capacity crunch. However, high aggregated energy consumption and increased inter-cell interference (ICI) caused by densification, remain the two long-standing problems. We propose a novel network orchestration solution for simultaneously minimizing energy consumption and ICI in ultra-dense 5G networks. The proposed solution builds on a big data analysis of over 10 million CDRs from a real network that shows there exists strong spatio-temporal predictability in real network traffic patterns. Leveraging this we develop a novel scheme to pro-actively schedule radio resources and small cell sleep cycles yielding substantial energy savings and reduced ICI, without compromising the users QoS. This scheme is derived by formulating a joint Energy Consumption and ICI minimization problem and solving it through a combination of linear binary integer programming, and progressive analysis based heuristic algorithm. Evaluations using: 1) a HetNet deployment designed for Milan city where big data analytics are used on real CDRs data from the Telecom Italia network to model traffic patterns, 2) NS-3 based Monte-Carlo simulations with synthetic Poisson traffic show that, compared to full frequency reuse and always on approach, in best case, proposed scheme can reduce energy consumption in HetNets to 1/8th while providing same or better Qo

A self-organized resource allocation scheme for heterogeneous macro-femto networks

This paper investigates the radio resource management (RRM) issues in a heterogeneous macro-femto network. The objective of femto deployment is to improve coverage, capacity, and experienced quality of service of indoor users. The location and density of user-deployed femtos is not known a-priori. This makes interference management crucial. In particular, with co-channel allocation (to improve resource utilization efficiency), RRM becomes involved because of both cross-layer and co-layer interference. In this paper, we review the resource allocation strategies available in the literature for heterogeneous macro-femto network. Then, we propose a self-organized resource allocation (SO-RA) scheme for an orthogonal frequency division multiple access based macro-femto network to mitigate co-layer interference in the downlink transmission. We compare its performance with the existing schemes like Reuse-1, adaptive frequency reuse (AFR), and AFR with power control (one of our proposed modification to AFR approach) in terms of 10 percentile user throughput and fairness to femto users. The performance of AFR with power control scheme matches closely with Reuse-1, while the SO-RA scheme achieves improved throughput and fairness performance. SO-RA scheme ensures minimum throughput guarantee to all femto users and exhibits better performance than the existing state-of-the-art resource allocation schemes

Future RAN architecture: SD-RAN through a general-purpose processing platform

In this article, we identify and study the potential of an integrated deployment solution for energy-efficient cellular networks combining the strengths of two very active current research themes: 1) software-defined radio access networks (SD-RANs) and 2) decoupled signaling and data transmissions, or beyond cellular green generation (BCG2) architecture, for enhanced energy efficiency. While SD-RAN envisions a decoupled centralized control plane and data-forwarding plane for flexible control, the BCG2 architecture calls for decoupling coverage from the capacity and coverage provided through an always-on low-power signaling node for a larger geographical area; the capacity is catered by various on-demand data nodes for maximum energy efficiency. In this article, we show that a combined approach that brings both specifications together can not only achieve greater benefits but also facilitate faster realization of both technologies. We propose the idea and design of a signaling controller that acts as a signaling node to provide always-on coverage, consuming low power, and at the same time host the control plane functions for the SDRAN through a general-purpose processing platform. The phantom cell concept is also a similar idea where a normal macrocell provides interference control to densely deployed small cells, although our initial results show that the integrated architecture has a much greater potential for energy savings than phantom cells